Children’s Eating Behaviors and Energy Intake: Overlapping Influences and Opportunities for Intervention

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Children’s Eating Behaviors and Energy Intake: Overlapping Influences and Opportunities for Intervention

Ciarán G. Forde, Anna Fogel, and Keri McCrickerd

Early-life factors combine to influence the development of childhood overweight/obesity [1], yet the eating behaviors that support a sustained positive energy balance and unhealthy growth outcomes are less clear. The transition from “risk” to childhood obesity operates largely through the emergence of maladaptive eating behaviors that consolidate during childhood, remain stable, and predict sustained higher energy intakes and adiposity [2]. We examined associations between eating behaviors, energy intake, and body composition among children from the GUSTO cohort (Growing Up in Singapore towards Healthy Outcomes). Measures were collected at 2 time points (4.5 and 6 years) and included premeal portion selection, within-meal coding of oral processing behaviors, and postmeal measures of food responsiveness, which were examined alongside measured parental feeding practices and parent reports of their child’s appetitive traits. 

Before lunch, children completed portion tasks on a computer, where they rated their appetite and then navigated through a series of food portion images to select their ideal portions of 8 familiar foods. Portions selected in the computer task significantly predicted the portions selected and consumed during a lunchtime meal. Children tended to pick more of foods they reported liking, but also smaller portions of foods they expected to be more filling, independently of whether they were liked. Importantly, the children who selected the largest portions tended to serve and consume a larger portion during the lunchtime meal. 

At the 4.5- and 6-year time points, behavioral coding was used to capture each bite, chew, and swallow during the lunch, to subsequently derive a series of oral processing behaviors associated with energy intake (Fig. 1). 

Children who ate at a faster rate (g/min) took larger bites, chewed less per bite, and consumed more energy at each meal (Fig. 2) [3, 4]. Faster eating rates at 4.5 years predicted faster eating and higher energy intakes at 6 years, with the same oral processing behaviors driving eating rates at both time points. Children who ate faster at 4.5 years also had higher adiposity at 6 years, emphasizing a role for these behaviors in prospective weight gain. Portion selection and eating rate independently predicted higher energy intakes, but children who chose the largest portions, had the longest meals, and ate at the fastest rates consumed the most energy, highlighting an important overlap in behaviors that contribute to higher energy intakes.

fig 1

Fig. 1. Example of the behavioral coding scheme used to measure withinmeal bites, chews, and swallows to characterize oral processing behaviors of the children.

 

Postmeal child responsivity to palatable food cues was assessed using the EAH paradigm (eating in the absence of hunger), where children were given free access to snacks after they had eaten to fullness. Children who demonstrated EAH consumed more energy cumulatively from lunch and the snack test [5]. This EAH behavior was consistent over time and linked to faster eating rates, highlighting an overlap between behaviors that contribute to higher energy intakes both within and outside the main meals. 

Importantly, parents appear to be aware of their child’s appetitive traits, with faster eating and greater intake significantly correlated with higher “food responsiveness” and “enjoyment of food” reported by the parents in the CEBQ (Child Eating Behavior Questionnaire) [6]. Some parents responded to their child’s behaviors during the meal by using feeding practices more frequently during the meal, particularly among girls. Despite this, children who were prompted more continued to eat quickly and consume more energy [7]. Our findings suggest a bidirectional relationship between parental feeding practices, child eating behaviors, and subsequent weight status.

fig 2

Fig. 2. Association between eating rate and energy intake during lunch (r2 = 0.38; p < 0·001; n = 386, adapted from Fogel et al. [3]).

Taken together, these findings highlight that higher energy intakes were consistently associated with a series of overlapping eating behaviors and parental feeding practices that were stable over time and most commonly found in children with highest BMIz scores. Our findings emphasize the need to go beyond targeting individual eating behaviors to consider the cumulative impact differences in energy selection, consumption, and associated parental feeding practices have on energy intake when developing interventions targeting children at risk of overweight or obesity.
 

References

  • Aris IM, Bernard JY, Chen LW, et al: Modifiable risk factors in the first 1000 days for subsequent risk of childhood overweight in an Asian cohort: significance of parental overweight status. Int J Obes (Lond) 2018;42:44–51.
  • Carnell S, Wardle J: Appetite and adiposity in children: evidence for a behavioral susceptibility theory of obesity. Am J Clin Nutr 2008;88:22–29.
  • Fogel A, Goh AT, Fries LR, et al: A description of an “obesogenic” eating style that promotes higher energy intake and is associated with greater adiposity in 4.5-yearold children: results from the GUSTO cohort. Physiol Behav 2017;176:107–116.
  • Fogel A, Goh AT, Fries LR, et al: Faster eating rates are associated with higher energy intakes during an ad libitum meal, higher BMI and greater adiposity among 4.5-yearold children: results from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. Br J Nutr 2017;117:1042–1051.
  • Fogel A, McCrickerd K, Fries LR, et al: Eating in the absence of hunger: stability over time and associations with eating behaviours and body composition in children. Physiol Behav 2018;192:82–89.
  • Fogel A, Fries LR, McCrickerd K, et al: Oral processing behaviours that promote children’s energy intake are associated with parent-reported appetitive traits: results from the GUSTO cohort. Appetite 2018;126:8–15.
  • Fogel A, Fries LR, McCrickerd K, et al: Prospective associations between parental feeding practices and children’s oral processing behaviours: results from the GUSTO cohort. Matern Child Nutr 2018, in press.

Abstract


The transition from risk factors in the first 1,000 days to childhood obesity occurs largely through the development of maladaptive eating behaviors that emerge early, remain stable, and support greater energy intake over time. We have examined the association between eating behaviors, energy intake, and body composition at 4.5 and 6 years of age among children from the GUSTO (Growing Up in Singapore towards Healthy Outcomes) cohort. Our findings demonstrate that when children select larger portions, eat at a faster rate, and continue to eat when sated, they consume more energy than children who do not exhibit these behaviors. We have shown that these behaviors are stable over time and independently predict higher adiposity and BMIscores at the later time point. We ob- served that faster eating and greater intakes were associated with parent report measures of appetitive traits, such as the child’s satiety responsiveness, food fussiness, and enjoyment of food. Importantly, faster eating rates mediated the link between these appetitive traits and child energy intakes. In addition, within-meal parental feeding practices were linked to a faster eating rate, higher energy intakes, and higher BMIscores in some children, suggesting that parents are aware of these eating behaviors and likely adapt their feeding practices to influence their child’s energy intake. These findings emphasize the need to consider the interaction and cumulative impact of these eating behaviors and parental feeding practices on children’s energy intake, and, consequently, the need to develop holistic intervention approaches that target the behaviors that contribute most to a child’s risk of developing overweight and obesity.
 

Introduction


Early-life risk factors within the first 1,000 days can cumulatively influence the development of childhood overweight and obesity. Risks such as parental weight status, breastfeeding duration, or the early introduction of solid foods have been associated with weight gain [1], and a recent analysis found that Singaporean children that had 4 or more of these risk factors were 11 times more likely to be overweight or obese at 4 years of age [2]. Associations between the early-life risk and the later development of overweight and obesity are well documented, yet the eating behaviors that support the sustained positive energy balance required for these unhealthy growth outcomes are less clear. The “behavioral susceptibility hypothesis” proposes that a genetic predisposition to become obese manifests through the development of “appetitive traits” linked with greater responsiveness to the food environment and poorer self-regulation that promotes increased energy intake [3]. In this regard, the transition from early-life “risk” to childhood obesity is likely to operate through the emergence of maladaptive eating behaviors that consolidate during childhood, remain stable over time, and predict weight gain and higher adiposity. These behaviors can overlap to influence food choice and energy intakes at every stage of a meal, from portion selection to eating behaviors within the meal, and postmeal appetite and responsivity to available food cues. A child’s food environment, food preferences, habitual energy intake behaviors, and growth outcomes are influenced by their caregivers through the foods they choose and the feeding practices they use [4, 5]. The association between caregiver feeding practices and children’s eating behaviors are likely bidirectional, and the feeding practices used by a caregiver to moderate food intake may also be influenced by the child’s appetitive traits and subsequent eating behaviors displayed [6]. This emphasizes the important role of caregivers and food environment in the behavioral transition from early-life risk to overweight and obesity.
The current paper provides a summary of a series of studies that investigated links between child eating behaviors and parental feeding practices, and their association with energy intake and body composition among children from the GUSTO (Growing Up in Singapore towards Healthy Outcomes) cohort. Since its inception in 2009, the GUSTO cohort has extensively profiled the growth and development of a large sample of Singaporean mother-child pairs (= 1,247). Eligibility criteria and the GUSTO study profile are described in detail elsewhere [7]. The findings reported are summarized from data collected at 2 time points (4.5 and 6 years) and focus on child portion selection, oral processing behaviors, within-meal energy intake, and postmeal measures of food responsivity, as well as measures of parental feeding practices and parent reports of child appetitive traits.

Child Portion Selection and Energy Intake


The amount of food selected at the start of a meal can strongly influence the total amount consumed [8], and although the factors that influence adult portion selection have been studied extensively [9], to date much less is known about how children differentiate between foods, or which factors govern the portion they select [10]. To address this, at the 6-year time point, we asked children (= 373: 197 boys and 193 girls) to complete a computer-based portion selection task where they made a series of judgments across a range of 8 different foods. Children were required to think about their feelings of hunger and fullness, and they were asked to make estimations of how filling different foods might be, as well as how much they liked them. After this, children estimated the portion of each food they would choose for a meal. They were then provided with one of the foods (fried rice) ad libitum and asked to serve themselves and consume as much or as little as they wanted for lunch. Using this approach, it was possible to com- pare the relative influence of different premeal beliefs on the portion selected and consumed during the meal [11]. Findings showed that the portions selected by children in the computer task significantly predicted the portion selected and consumed during the lunchtime meal. Children selected larger portions of the foods they liked, but they also appeared to consider the filling properties of different foods by selecting smaller portions of foods they regarded to be more filling and larger portions of foods they believed were less filling independently of how much they liked the food. The amount of food chosen during the lunchtime meal was the strongest predictor of the actual energy intake, with children who selected larger portions eating more, highlighting the tendency for children to eat in response to the portions they are served. These findings are important as they demonstrate that children at this age are not simply choosing larger portions of foods they like but are also capable of discriminating between foods based on their filling properties. The tendency to select larger portions at this age is linked with greater energy consumption, supporting the idea that guiding appropriate food portion selection is an important locus in the control of a child’s energy intake.
 

Eating Rate and Energy Intake at 4.5 and 6 Years


Although children’s appetitive traits are expressed through their premeal portion decisions, they can also be seen in the oral processing behaviors they exhibit within a meal. Previous research has demonstrated associations between the oral processing behaviors that promote greater energy intakes within a meal and child BMI [12, 13]. To further investigate these links between portion selection, oral processing behaviors, and energy intake, children at both 4.5 and 6 years participated in an ad libitum lunchtime meal (= 263: 133 boys and 130 girls) as a measure of their usual energy intakes. The test meals were video recorded at both time points, and using behavioral coding we derived a series of oral processing behaviors for comparison with energy intake based on a previously published approach [14]. Figure 1 shows an exemplary screenshot of a video recording and a coding scheme used. This approach enabled a comparison of differences in the oral processing behaviors exhibited during the meal to explore whether these behaviors were associated with differences in child energy intakes and body composition at each time point.
Children who ate their meal at a faster rate (g/min) consumed significantly more energy than children who ate their meal slower [15] (Fig. 2). However, eating rate was specific to the time children had food in their mouth, and a comparison of the joint impact of eating rate and total meal duration (min) showed that the children who ate faster and for a longer duration consumed the most energy. 
Closer inspection of the oral processing characteristics exhibited by faster- eating children showed that children who eat faster tend to have a larger average bite size (g), chewing each bite in fewer cycles and through this producing a shorter average orosensory exposure to the food during each mouthful (Fig. 3). Comparison of microstructural patterns of eating at the 6-year time point demonstrated that the same oral processing behaviors were driving faster eating rates and greater energy intakes at both time points in what we have described as an “obesogenic” eating style that encourages greater food intake within a meal [16]. When children were median split into faster- and slower-eating groups at 4.5 years, we found that children in the faster-eating group consumed on average 75% more energy within the same lunchtime meal than children in the slower group [15]. These acute differences in energy intake were also associated with differences in child body composition at 4.5 years, as children in the faster-eating group had significantly higher BMIscores and higher skinfold adiposity indices, and a subset of children who had abdominal MRI scan (= 158) had a higher volume of subcutaneous abdominal adiposity [15]. When the same children were followed to the 6-year time point, it was clear that these behaviors remained stable and again predicted greater energy intake during the lunchtime meal. Being a faster eater at 4.5 years was a significant predictor of being a faster eater at 6 years, and children who ate faster at 4.5 years had higher BMIscores and adiposity at 6 years [17]. These findings emphasize the stability of oral processing behaviors and the importance of these behaviors in promoting greater energy intake and weight gain.
The selection of larger portions and eating at a faster rate were both significant independent predictors of higher energy intakes among children. However, these eating behaviors were also found to interact, such that children who chose larger portions and ate at a faster rate consumed the most energy within the meal [18], highlighting the combined impact of larger portions and eating quickly in promoting energy intake. Interventions focused on reducing eating rate alone may have limited success if they do not also account for the risk of increased energy intake arising from the selection of larger portions. Specific oral processing behaviors, such as a large bite size, appear to be stable over time and, when ob- served in children at 4.5 years, were capable of predicting changes in body com- position at the later time point. Taken together, these findings are important because they suggest several loci for potential intervention, where it may be possible to reduce the impact of multiple behaviors on energy intakes both in terms of monitoring child-selected portions and potentially using meal properties, such as food textures, to target the specific oral processing behaviors that promote faster eating [19]. Considering the independent and combined impact of these overlapping behavioral risks, intervention strategies should take an integrated approach accounting for both premeal portion selection and within-meal eating behavior to control both energy selection and intake [18].

fig 1
Fig. 1. Example of the behavioral coding scheme used to measure within-meal bites, chews, and swallows to characterize oral processing behaviors of the children.

fig 2
Fig. 2. Association between eating rate and energy intake during lunch (r2 = 0.38, p <   0 · 001; n = 386) (adapted from Fogel et al. [16]).


fig 3

Fig. 3. Summary of oral processing behaviors that predict greater energy intakes at 4.5 and 6 years of age (all significant at p < 0.001).
 

Eating in the Absence of Hunger and Child Inhibitory Control
 

Beyond main meals, children are susceptible to increase their energy intake when palatable snacks are available in their food environment even when a child is fully sated. The tendency to eat in the absence of hunger (EAH) is a measure of food cue responsivity and has previously been shown to contribute to the increased energy intakes associated with overweight and obesity among children [20]. To study differences in EAH among GUSTO children, a subset (= 255: 127 boys and 128 girls) were given free access to snacks after they reported feeling full following the lunchtime meal at both the 4.5- and 6-year time points. Children were classified into those that did or did not exhibit EAH behaviors, and the quantity of calories consumed from their snack intake during the EAH task was recorded. Results showed that children who demonstrated EAH did not differ in the energy consumed at lunch from children who did not show EAH. However, children who demonstrated EAH consumed more energy cumulatively when intake was combined from the lunch and the EAH snack test at both 4.5 and 6 years [21]. In addition, children who exhibited EAH at the earlier time point were 3 times more likely to continue this behavior at the 6-year time point, indicating consistency in this behavior and a potential sustained contribution to greater energy intakes. Despite this, there was no association between children’s tendency to EAH and their BMI or adiposity at either time point, suggesting the link between EAH and child growth outcomes might manifest at an older age.
The eating behaviors we have identified to predict higher energy intakes tend to be stable over time and often overlap within the same group of children. This may be due to common underlying mechanisms that predispose some children to be more vulnerable to increased energy intakes than others. For example, children who show EAH may be less able to control an impulse to respond to food cues even when sated. Previous research has shown that children who have high- er inhibitory control are less likely to be overweight than children who do not show the same capacity for self-regulation [22]. In the context of eating behavior, inhibitory control relates to the ability to stop or suppress certain responses to food cues in the environment. A higher propensity to EAH is a good behavioral measure of a child’s responsivity to food cues and may be one of the mechanisms through which a lower inhibitory control predisposes children to in- crease their energy intake and eventually promote weight gain [23]. We investigated whether individual differences in inhibitory control were linked to the identified differences in child eating behaviors that promote greater intake, such as the selection of larger portions, faster eating rates, and EAH. Children at 6 years completed a measure of inhibitory control known as the stop signal task, which gauges a child’s capacity to voluntarily inhibit or regulate their attentional and behavioral responses (CANTAB; Cambridge Cognition 2017). Children that had lower inhibitory control and were more restless during the stop signal task were the same children that tended to EAH, suggesting a relationship between this trait and energy intakes from snacks [24]. Importantly, further associations were found where children with lower inhibitory control also selected larger food portions on the computer portion task and ate food at a faster rate during the meal [24]. These results suggest a convergence of some eating behaviors associated with greater energy intakes among children with lower inhibitory control that reflects the way they select and consume their portions and respond to food cues in their environment. This overlap in behaviors is predicted to drive weight gain, and identifying children with lower inhibitory control and the associated food intake behaviors may help in the development of strategies to mitigate this obesity risk.

 

Parental Influences on Child Eating Behaviors and Energy Intake

A wide range of eating behaviors have been shown to increase children’s energy intakes and promote weight gain, and it is important to consider that these behaviors emerge in the home food environment, where one of the strongest factors shaping their development and expression is the influence of a child’s caregivers. During the preschool years, parent’s dietary habits, portion selection, and feeding practices around mealtimes play a significant role in influencing children’s experience with foods, which in turn shapes their eating behaviors. For example, the additional energy consumed when children have the opportunity to EAH relies on these snacks being made available in the child’s food environment in the first place. Moreover, energy intake from EAH is likely to be moderated by the caregiver’s feeding practices. The foods and portions a parent or caregiver selects for their child can significantly influence energy intake, with larger portions promoting greater consumption [25]. When parents in our cohort were asked to choose portions for their child, they tended to select larger portions for meals they had chosen in large portions for themselves, and they picked larger portions for their child if they believed the child liked that food [11]. This indicates that parents may base portion choices for their child on their own beliefs about foods and rely less on adapting portions to their child’s needs. This raises concerns that parental biases towards selecting larger portions for themselves may translate into habitually selecting larger portions for their child, which in turn may influence a child’s longer-term perception of appropriate portion size [10].
In addition to selecting a child’s food and portions, parents often use feeding practices during mealtimes to encourage, modify, or restrict food intake. Research has shown that restricting energy-dense palatable foods and using more controlling feeding practices can be counterproductive and lead to higher energy intakes and weight gain over time [26]. We investigated whether parents in our cohort were aware of their child’s appetitive traits. Parents who reported their child to have higher food approach (enjoyment of food or food responsiveness) and lower food avoidance (i.e., satiety responsiveness and fussy eating) behaviors had children who consistently consumed greater energy and had higher BMIand adiposity scores [27]. Faster eating rates were found to mediate the relationship between appetitive traits and higher energy intakes, such that children who had traits associated with greater energy intakes consumed more energy when they also ate at a faster rate [28]. This finding suggests that eating rate may be one of the behavioral pathways through which stronger appetitive traits manifest to promote energy intakes, and that mothers are noticing these behaviors in their children.
Finding that parents are somewhat aware of the eating behaviors linked to certain appetitive traits in their children suggests that they might use their feeding practices to try and modify them. Therefore, we investigated whether mothers’ use of feeding practices was linked with their child’s oral processing behaviors and increased energy intakes. To do this, we explored the relationship between the type and frequency of parental feeding practices (e.g., prompts, restrictions, and encouragements) and child eating behavior in a subset (= 155) of child-mother pairs [29]. Children that experienced the  most frequent feeding practices during the meal ate at a faster rate and con- sumed significantly more energy than children who experienced less-frequent feeding practices. However, this was not the same across both genders, as girls who displayed faster eating rates were more likely to experience parental feeding practices than boys who exhibited the same eating style. The frequency of parental feeding practices and child faster eating rates independently predicted greater energy intakes; however, children who ate faster and also experienced the highest frequency of feeding practices had the greatest energy in- takes, suggesting that parental influence did little to reduce eating rate or energy intake within the meal. This remained the case at 6 years, where prospective analyses showed that those children who were more frequently prompted at age 4.5 years had continued to have faster eating rates at 6 years [29].
Taken together, these findings stress the importance of considering how parental influences can impact the child’s food environment and moderate the expression of eating behaviors associated with greater energy intakes. Caregivers can have a powerful short-term impact on their child’s energy consumption and the potential to exert a longer-term impact on the development of child food and portion selection, as well as the eating styles that can increase energy intake within meals [29]. Rather than selecting portions and encouraging intake based on the parent’s feeding goals, parents are encouraged to apply responsive feeding practices where appropriate foods are provided based on awareness of and sensitivity to a child’s appetite need state [10].

Conclusions: Future Opportunities for Integrated Behavioral Interventions


Our findings highlight associations between higher energy intakes and a series of overlapping and interrelated eating behaviors and parental feeding practices. We have identified behaviors such as selecting large portions, eating at a faster rate, and EAH consistently predicted greater energy intakes. An opportunity exists to moderate energy intakes by providing guidance to parents and children on the appropriate portions to select or by reducing the availability of larger portions for children in general. Insights into the oral processing behaviors that underpin faster eating rates create new opportunities to develop foods that encourage smaller bite size, increase chews per bite, and result in a natural slowing of eating rates in response to the food textures experienced during consumption [30, 31]. Future research should consider combining approaches in the design of food portions and textures for children with appetitive traits and eating behaviors that increase their risk of increased energy intakes over time.
The eating behaviors identified have been shown to independently predict higher energy intakes, but when combined they often increase the risk of energy overconsumption and subsequent weight gain. Each risk in isolation may periodically lead to a positive energy balance, but, cumulatively, these risks combine to sustain a positive energy balance and promote increased weight gain throughout childhood. The interplay between eating behaviors and feeding practices is important to consider, and it highlights the potential for aberrant eating behaviors to be exacerbated when energy intake is informed by factors unrelated to a child’s appetite need state. Understanding how portion selection and eating behavior is moderated by parental feeding practices can help improve our ability to identify children at risk of developing obesity and advance the development of integrated approaches that target specific elements of a child’s behavior, their food environment, and their parent’s feeding practices.
The eating behaviors and feeding practices discussed in the current chapter can each contribute to increases in energy intakes, but in combination they are likely to have the greatest impact on energy intake, e.g., to consume quickly larger portions of higher-energy-dense foods. Attempts to modify a child’s eating rate are likely to be unsuccessful if they do not also consider the portion selection or parental feeding practices that also encourage greater energy intake within meals. These findings underscore the need to go beyond targeting individual eating behaviors and to consider holistic interventions that focus on the cumulative impact of energy selection, eating styles, and feeding practices that moderate these behavioral outcomes in the child.
 

References

  • 1 Reilly JJ, Armstrong J, Dorosty AR, et al: Ear- ly life risk factors for obesity in childhood: cohort study. BMJ 2005;330:1357.

  • 2 Aris IM, Bernard JY, Chen LW, et al: Modifi- able risk factors in the first 1000 days for subsequent risk of childhood overweight in an Asian cohort: significance of parental over- weight status. Int J Obes (Lond) 2018;42:44– 51.

  • 3 Carnell S, Wardle J: Appetite and adiposity in children: evidence for a behavioral susceptibility theory of obesity. Am J Clin Nutr 2008; 88:22–29.

  • 4 Wardle J, Cooke L: Genetic and environmental determinants of children’s food preferences. Br J Nutr 2008;99(suppl 1):S15–S21.

  • 5 Shloim N, Edelson LR, Martin N, Hetherington MM: Parenting styles, feeding styles, feeding practices, and weight status in 4–12 year-old children: a systematic review of the literature. Front Psychol 2015;6:1849.

  • 6 Jansen PW, de Barse LM, Jaddoe VWV, et al: Bi-directional associations between child fussy eating and parents’ pressure to eat: who influences whom? Physiol Behav 2017;176: 101–106.

  • 7 Soh SE, Tint MT, Gluckman PD, et al: Cohort profile: Growing Up in Singapore To- wards healthy Outcomes (GUSTO) birth cohort study. Int J Epidemiol 2014;43: 1401–1409.

  • 8 McCrickerd K, Leong C, Forde CG: Pre-school children’s sensitivity to teacher-served portion size is linked to age related differences in leftovers. Appetite 2017;114:320–328.

  • 9 Forde CG, Almiron-Roig E, Brunstrom JM: Expected satiety: application to weight management and understanding energy selection in humans. Curr Obes Rep 2015;4:131–140.

  • 10 McCrickerd K, Forde CG: Parents, portions and potential distortions: unpicking children’s meal size. Nutr Bull 2016;41:67–71.

  • 11 McCrickerd K, Forde CG: Determinants of mother and child selected portions; results from the GUSTO cohort. 25th Annual Society for the Study of Ingestive Behaviour Meeting, Montreal, July 18–22, 2017.

  • 12 Llewellyn CH, van Jaarsveld CH, Boniface D, et al: Eating rate is a heritable phenotype related to weight in children. Am J Clin Nutr 2008;88:1560–1566.

  • 13 Berkowitz RI, Moore RH, Faith MS, et al: Identification of an obese eating style in 4‐ year‐old children born at high and low risk for obesity. Obesity (Silver Spring) 2010;18: 505–512.

  • 14 Forde C, Leong C, Chia-Ming E, McCrickerd K: Fast or slow-foods? Describing natural variations in oral processing characteristics across a wide range of Asian foods. Food Funct 2017;8:595–606.

  • 15 Fogel A, Goh AT, Fries LR, et al: Faster eating rates are associated with higher energy in- takes during an ad libitum meal, higher BMI and greater adiposity among 4.5-year-old children: results from the Growing Up in Sin- gapore Towards healthy Outcomes (GUSTO) cohort. Br J Nutr 2017;117:1042–1051.

  • 16 Fogel A, Goh AT, Fries LR, et al: A descrip- tion of an “obesogenic” eating style that pro- motes higher energy intake and is associated with greater adiposity in 4.5-year-old children: results from the GUSTO cohort. Physiol Behav 2017;176:107–116.

  • 17 McCrickerd K, Fogel A, Goh AT, et al: Faster eating rates are stable over time and predict prospective increases in fat mass: results from the GUSTO Cohort. 25th Annual Society for the Study of Ingestive Behaviour Meeting, Montreal, July 18–22, 2017.

  • 18 McCrickerd K, Fogel A, Goh AT, et al: Faster eating predicts prospective portion selection and intake in pre-school age children: results from the GUSTO Cohort. 25th Annual Society for the Study of Ingestive Behaviour Meeting, Montreal, July 18–22, 2017.

  • 19 Bolhuis DP, Forde CG, Cheng Y, et al: Slow food: sustained impact of harder foods on the reduction in energy intake over the course of the day. PLoS One 2014;9:e93370.

  • 20 Fisher JO, Birch LL: Eating in the absence of hunger and overweight in girls from 5 to 7 years of age. Am J Clin Nutr 2002;76:226– 231.

  • 21 Fogel A, McCrickerd K, Fries LR, et al: Eating in the absence of hunger: stability over time and associations with eating behaviours and body composition in children. Physiol Behav 2018;192:82–89.

  • 22 Tan CC, Holub SC: Children’s self-regulation in eating: associations with inhibitory control and parents’ feeding behavior. J Pediatr Psy- chol 2010;36:340–345.

  • 23 Francis LA, Susman EJ: Self-regulation and rapid weight gain in children from age 3 to 12 years. Arch Pediatr Adolesc Med 2009;163: 297–302.

  • 24 Fogel A, McCrickerd K, Goh AT, et al: Associations between inhibitory control, eating behaviours and adiposity in 6-year-old children: results from the GUSTO cohort. Int J Obes 2019, in press.

  • 25 Johnson SL, Hughes SO, Cui X, et al: Portion sizes for children are predicted by parental characteristics and the amounts parents serve themselves. Am J Clin Nutr 2014;99:763–770.

  • 26 Birch LL, Fisher JO, Davison KK: Learning to overeat: maternal use of restrictive feeding practices promotes girls’ eating in the absence of hunger. Am J Clin Nutr 2003;78:215–220.

  • 27 Quah PL, Fries LR, Chan MJ, et al: Validation of the children’s eating behavior questionnaire in 5 and 6 year-old children from a multi-ethnic Asian population: the GUSTO cohort study.

  • 28 Fogel A, Fries LR, McCrickerd K, et al: Oral processing behaviours that promote children’s energy intake are associated with parent-reported appetitive traits: results from the GUSTO cohort. Appetite 2018;126:8–15.

  • 29 Fogel A, Fries L, McCrickerd K, et al: Prospective associations between parental feeding practices and children's oral processing behaviours: results from the GUSTO cohort. Matern Child Nutr 2018, in press.

  • 30 McCrickerd K, Lim CM, Leong C, et al: Texture-based differences in eating rate reduce the impact of increased energy density and large portions on meal size in adults. J Nutr 2017;147:1208–1217.

  • 31 Forde CG, van Kuijk N, Thaler T, et al: Texture and savoury taste influences on food in- take in a realistic hot lunch time meal. Appetite 2013;60:180–186.